Traffic sign recognition (TSR) is a technology which makes vehicles capable of recognizing the traffic signs appearing in the vicinity of the driving path. TSR systems form an important part of the ADAS (advanced driver assistance systems) that is currently being deployed in the cars of today. It is a classic example of rigid object detection. TSR systems depend on forward facing image sensors. Current TSR systems are aimed to assist the driver in the driving process. But, in the future, TSR systems will play a very crucial role in the functioning of autonomous cars.
Computers face a lot of challenges in identifying traffic signs in images due to the following reasons:
Within-class variability: the same traffic sign in the real world can give rise to different images due to:                a. Different viewing positions and different distances between the camera and traffic sign positions, and        b. Photometric effects: positions of multiple different light sources, their color, distribution of shadows, and view obstruction by objects present near the traffic signs.        
Between-class similarity: different classes of traffic signs may look very much alike.
Background objects in cluttered urban environments also pose a challenge.
Motion blur in images.
Faded, bent, and dirty sign boards.
Adverse weather conditions like rain and snow.
Traffic signs may also be slightly different from country to country. For example, speed limit traffic signs in some European countries are round with a red circle boundary, while in the US they are rectangular in shape.